偉大篩選器：為何即使有AI，大多數開發團隊仍難以達到高績效

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The Great Filter (Or Why High Performance Still Eludes Most Dev Teams, Even With AI)

In my post about The Gorman Paradox, I compare the lack of any evidence of “AI”-assisted productivity gains to be found out here in the Real WorldTM with the famous Fermi Paradox that asks, if the universe is teeming with intelligent life, where is everybody?

It’s been over 3 years, and we’ve seen no uptick in products being added to the app stores. We’ve seen no rising tide on business bottom lines. We’ve seen no impact on national GDPs.

There is a likely explanation, and it’s the most obvious one: “AI”-assisted coding doesn’t actually make the majority of dev teams more productive. For sure, it produces more code. But, on average, it creates no net additional value.

The DORA data does find some teams reaping modest gains in terms of software delivery lead times without sacrificing reliability, and – interestingly – the data shows that those high-performing teams using “AI” were already high-performing without it.

The majority of teams showed that “AI” actually slowed them down, and these were the teams who were already pretty slow before “AI”. Attaching a code-generating firehose to the process just made them marginally slower.

The differentiator? Are the high-performing teams super-skilled programmers? Are they getting paid more? Are they putting something in the office water supply?

It turns out that what separates the teams who get a negative boost from the teams who get a positive boost is that the latter have addressed the bottlenecks in their development process.

Blocking activities, like detailed up-front design, after-the-fact testing, Pull Request code reviews, and big merges to the main branch, have been turned into continuous activities.

Teams work in much smaller batches and in much tighter feedback loops, designing, testing, inspecting and merging many times an hour instead of every few days.

Work doesn’t sit in queues waiting for someone’s attention. There are very few traffic lights between the developer’s desktop and the outside world to slow that traffic down.

And this means that changes can make it into the hands of users very rapidly, with highly automated, highly reliable, frictionless delivery pipelines that – as the supermarket ads used to say – get the peas from the farmer’s field to your table in no time at all.

The just-in-time grocery supply chains of supermarkets are a good analogy for the processes high-performing teams are using. Supermarkets don’t buy a year’s supply of fresh peas once a year. They buy tomorrow’s supply today, and their formidable logistical capabilities get those peas on the shelves pronto.

Those formidable logistical capabilities didn’t just appear, either. They’re the product of many decades of investment. Supermarket chains have sunk billions into getting better at it, so they can maximise cash flow by minimising the amount of working capital they have committed at any time.

They don’t want millions of pounds-worth of produce sitting in warehouses making them no money.

And businesses don’t want millions of pounds-worth of software changes sitting in queues waiting to be released. They want them out there in the hands of users, creating value in the form of learning what works and what doesn’t. Software that can’t be used has no value.

Walk into any large organisation and take a snapshot of how much investment in developed code is “in progress”. For some, it literally is million of pounds-worth – tens or hundreds of thousands of pounds, multiplied by dozens or hundreds of teams.

The impact on a business of being able to out-learn the competition can be so profound, we might ask ourselves “Why isn’t everybody doing this?” Can you imagine a supermarket chain deciding not to bother with JIT supply? They wouldn’t last long.

It’s come into focus even more sharply with the rise of “AI”-assisted software development. It’s quite clear now that even modest productivity gains lie on the other side of the spectrum with teams who have addressed their bottlenecks and have low-friction delivery pipelines.

I see a “Great Filter” that continues to prevent the large majority of dev teams making it to that Nirvana. It requires a big, ongoing investment in the software development capability needed.

We’re talking about investment in people and skills. We’re talking about investment in teams and organisational design. We’re talking about investment in tooling and automation. We’re talking about investment in research and experimentation. We’re talking about investment in talent pipelines and outreach. We’re talking about investment in developer communities and the profession of software development.

Typically, I’ve seen that companies who manage to progress from the bottleneck-ridden ways of working to highly iterative, frictionless methods needed to invest 20-25% of their entire development budget in building and maintaining that capability.

And building that kind of capability takes years.

You can’t buy it. You can’t install it. You can’t have it flown in fresh from Silicon Valley.

And, like organ transplants, any attempt to transplant that kind of capability into your business will be met with organisational anti-bodies protecting the status quo.

And that, folks, is The Great Filter.

Most organisations are simply not prepared to make that kind of commitment in time, effort and money.

Sure, they want the business benefits of faster lead times, more reliable releases, and a lower cost of change. But they’re just not willing to pony up to get it.

On a daily basis, I see people online warning us not to “get left behind by AI”. The reality is that the people who really are getting left behind are the ones who think that the bottlenecks and blockers they’ve struggled with in the past will magically get out of the way of the code-generating firehose.

Low-performing teams, now grappling with the downstream chaos caused by “AI” code generation, will probably always be the norm. And the value of this technology will probably never be realised by those businesses.

If you’re on of the few who are serious about building software development capability, my training courses in the technical practices that enable rapid, reliable and sustained evolution of software to meeting changing needs are half price if you confirm your booking by Jan 31st.

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Author: codemanship

Founder of Codemanship Ltd and code craft coach and trainer
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